Embodiments of the disclosure relate to image sensors and in particular to a method and a device for obtaining high resolution images from low resolution image sensors.
Gaze tracking is typically used in computer interfaces to increase interaction between a user and a computer. It aims at providing the coordinates of a point or of a set of points (i.e. a path) in a reference frame, typically a reference frame associated with images obtained through an image sensor. Such a point or a path can be used for numerous applications such as selecting an object in a graphical user interface, identifying a target in a flight simulator, or diagnosing visual disorders.
According to a particular implementation, an infrared beam illuminates an eye to obtain bright pupils and the reflected beam is picked up by an image sensor. The resulting images are then processed to detect the location of the reflected beam in the images. Knowing the location of the infrared beam source and of the image sensor enables a gaze point to be determined.
Sometimes, an aperture of f/6 is used to provide a tradeoff between diffraction and depth of field (DoF), and the pixel size of the image sensor is about 3 μm to optimize density and sensitivity.
As set forth in the thesis entitled “Eye Gaze Tracking for Human Computer Interaction” (Heiko Drewes, 2010, Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics), it is commonly accepted that the user's eyes requires about 100 pixels resolution for tracking the representation of an iris, of which the average size (irissize) is about 11 mm.
When considering a horizontal field of view (FoV) of 50° and a distance of 40 cm between the user's eyes and a display (with which an image sensor is associated), the horizontal field of view (FoVsize) corresponds to about 37 cm on that display.
Accordingly, the number of pixels (nbpixels) required for a field of view of 50° at a distance of 40 cm, i.e. the image sensor width, can be expressed as follows:
      nb    pixels    =                    resolution                  iris          size                    ×              FoV        size              =                            100          11                ×        370            ≈              3        ⁢                  ,                ⁢        400            
Such a number of pixels makes it possible to cover the whole horizontal area of 37 cm facing the sensor and get a resolution of 100 pixels for an object having a size of 11 mm.
As a result, considering a pixel width of 3 μm, the image sensor width is about 10.2 mm (3,400×3 μm).
For a field of view approximately equal to 50° and an image sensor width (Swidth) equal to 10.2 mm, the focal distance (f) of the lens is about 11 mm:
  f  =                    S        width                    2        ⁢                  tan          ⁡                      (                          FoV              2                        )                                =                  10.2                  2          ⁢                      tan            ⁡                          (                              50                2                            )                                          ≈      11      
For reference, an 11 mm lens with an aperture of f/6 provides a depth of field (DoF) of about 6.2 cm at 40 cm.
However, although such an optical system may make it possible to track eyes, it presents drawbacks. In particular, a 10.2 mm width image sensor with pixel width of 3 μm is indeed expensive.
As a consequence, there is a need for providing optical systems capable of acquiring high resolution images, using low resolution image sensors, in particular to allow efficient implementation of tracking algorithms at a reasonable price.